Pipelines, e.g. those used in the oil and gas industry, need regular inspection and maintenance before potentially costly failures occur. A traditional method of assessing the technical condition of a pipeline typically includes flaw detection using in-line inspection (ILI) for detecting location and evaluating parameters of separate metal defects, joining defects into clusters by an expert evaluation method (without indicating the rules of joining), calculating a level of stress-deformed condition (SDC) in cluster zones to assess their danger, and calculating a permissible operating pressure and evaluated factor of repair (EFR) for clusters of corrosion origin based on residual pipe wall thickness with defects of “metal loss” (corrosion) type.
However, there are several limitations to the above method. For example, ILI using intelligent pigging is unavailable for a range of objects that are non-piggable, or requires significant spending to prepare an object for pigs running. While the ILI method is suitable for the first task (the flaw detection itself), it is less advantageous for evaluating the comparative degree of the flaw's danger (e.g. by ranking), or for calculating serviceability of pipeline sections with various defects. Also, traditional calculations consist only in the evaluation of danger of groups of defects (clusters) like “metal loss”. The task of evaluating the corrosion rate (corrosion prognosis or monitoring) is not solved, and is typically settled by repeated runs of tools-defectoscopes.
Furthermore, in the above traditional method, there is no evaluation of cracks stability, that is, no prognosis for the rate of crack-like defects development, especially in a longitudinal direction. There is also no evaluation of danger of other types of defects (e.g. welds) due to operation conditions, as the evaluation of metal properties degradation in aggressive conditions and with anomalies of stress-deformed condition (SDC) is not carried out. For example, there are pipeline sections with sags, bends, stresses/stretches/twists, that is, with loss of a pipeline stability, e.g. due to land-washing during heavy rains, in land-slipping areas, precipices, ravines and zones of seismic activity. In addition, the main problem—the degree of stress concentration in a particular pipeline section—is not considered; it must be considered by engineers of the integrity department of the company/operator by e.g. expert evaluation.
As an alternative to the above method, a magnetometric tomography method (MTM) has been proposed. MTM is a non-contact method of non-destructive testing (NDT) and technical diagnostics based on remote scanning the magnetic field of a ferro-magnetic pipeline in a system of orthogonal coordinates. Additionally, manual processing and calibrating are used to define locations of sections with metal defects of various types, identify the type of the most dangerous defects, and evaluate serviceability of defective sections according to the degree of mechanical stress concentration.
However, MTM is currently available only to on-shore (i.e. land-based) applications. Also, the current detection capability of such a magnetometer is only up to a maximum distance of 20 times the pipe diameter. Thus, such conventional MTM systems are not suitable for many subsea (i.e. underwater) pipelines, which may be located at significant depths. The inspection speed is also limited to only about 2 meters per second (m/s), and the recording of distance is typically manual. Also, the analysis of the collected data is substantially manual, i.e. it relies again on expert evaluation.
A need therefore exists to provide a system and method for inspecting a subsea pipeline that seeks to address at least some of the above problems.